Sequence signatures within the genome of SARS-CoV-2 can be used to predict host source.

We conducted an in silico analysis to better understand the potential factors impacting host adaptation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in white-tailed deer, humans, and mink due to the strong evidence of sustained transmission within these hosts. Classification models trained on single nucleotide and amino acid differences between samples effectively identified white-tailed deer-, human-, and mink-derived SARS-CoV-2. For example, the balanced accuracy score of Extremely Randomized Trees classifiers was 0.984 ± 0.006. Eighty-eight commonly identified predictive mutations are found at sites under strong positive and negative selective pressure. A large fraction of sites under selection (86.9%) or identified by machine learning (87.1%) are found in genes other than the spike. Some locations encoded by these gene regions are predicted to be B- and T-cell epitopes or are implicated in modulating the immune response suggesting that host adaptation may involve the evasion of the host immune system, modulation of the class-I major-histocompatibility complex, and the diminished recognition of immune epitopes by CD8+ T cells. Our selection and machine learning analysis also identified that silent mutations, such as C7303T and C9430T, play an important role in discriminating deer-derived samples across multiple clades. Finally, our investigation into the origin of the B.1.641 lineage from white-tailed deer in Canada discovered an additional human sequence from Michigan related to the B.1.641 lineage sampled near the emergence of this lineage. These findings demonstrate that machine-learning approaches can be used in combination with evolutionary genomics to identify factors possibly involved in the cross-species transmission of viruses and the emergence of novel viral lineages.IMPORTANCESevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible virus capable of infecting and establishing itself in human and wildlife populations, such as white-tailed deer. This fact highlights the importance of developing novel ways to identify genetic factors that contribute to its spread and adaptation to new host species. This is especially important since these populations can serve as reservoirs that potentially facilitate the re-introduction of new variants into human populations. In this study, we apply machine learning and phylogenetic methods to uncover biomarkers of SARS-CoV-2 adaptation in mink and white-tailed deer. We find evidence demonstrating that both non-synonymous and silent mutations can be used to differentiate animal-derived sequences from human-derived ones and each other. This evidence also suggests that host adaptation involves the evasion of the immune system and the suppression of antigen presentation. Finally, the methods developed here are general and can be used to investigate host adaptation in viruses other than SARS-CoV-2.

Whole-genome sequencing of SARS-CoV-2 from the initial cases of domestic cat infections in Canada.

Two cat nasal swabs from Canada's earliest confirmed SARS-CoV-2 positive domestic cats were sequenced to over 99% SARS-CoV-2 genome coverage. One cat had lineage A.23.1 SARS-CoV-2 not reported before in animals. Both sequences have multiple spike gene mutations and clustered closely with human-derived sequences in the global SARS-CoV-2 phylogenetic tree.

Genomic and transcriptomic characterization of delta SARS-CoV-2 infection in free-ranging white-tailed deer (Odocoileus virginianus).

White-tailed deer (WTD) are susceptible to SARS-CoV-2 and represent an important species for surveillance. Samples from WTD (n = 258) collected in November 2021 from Québec, Canada were analyzed for SARS-CoV-2 RNA. We employed viral genomics and host transcriptomics to further characterize infection and investigate host response. We detected Delta SARS-CoV-2 (B.1.617.2) in WTD from the Estrie region; sequences clustered with human sequences from October 2021 from Vermont, USA, which borders this region. Mutations in the S-gene and a deletion in ORF8 were detected. Host expression patterns in SARS-CoV-2 infected WTD were associated with the innate immune response, including signaling pathways related to anti-viral, pro- and anti-inflammatory signaling, and host damage. We found limited correlation between genes associated with innate immune response from human and WTD nasal samples, suggesting differences in responses to SARS-CoV-2 infection. Our findings provide preliminary insights into host response to SARS-CoV-2 infection in naturally infected WTD.

Adenoviral hemorrhagic disease in a farmed elk (Cervus canadensis) in Alberta, Canada.

Adenoviral hemorrhagic disease (AHD), caused by deer atadenovirus A (OdAdV-1), affects captive and free-ranging cervids across North America. Here we present a case of AHD in a 6-month-old female elk calf from a farm in Alberta. Histopathology revealed multisystemic vasculitis with endothelial intranuclear inclusion bodies, pulmonary hemorrhage, and small intestinal hemorrhage characteristic of the acute systemic form of AHD. Immunohistochemistry was positive for OdAdV-1, confirming the diagnosis. Whole-genome sequencing of the virus was conducted for phylogenetic comparison. This is the 1st reported case of AHD in a farmed elk in Canada and the 1st reported case in an elk in Alberta. Key clinical message: Adenoviral hemorrhagic disease (AHD) is an emerging disease that should be investigated as a top differential when diagnosticians and veterinarians encounter young cervids found dead with pulmonary edema or hemorrhage and/or hemorrhagic enteropathy.

Maladie hémorragique adénovirale chez un wapiti d'élevage (Cervus canadensis) en Alberta, Canada. La maladie hémorragique adénovirale (AHD), causée par l'atadénovirus A du cerf (OdAdV-1), affecte les cervidés en captivité et en liberté partout en Amérique du Nord. Nous présentons ici un cas d'AHD chez un wapiti femelle de 6 mois d'une ferme en Alberta. L'histopathologie a révélé une vascularite multi-systémique avec des corps d'inclusion intranucléaires endothéliaux, une hémorragie pulmonaire et une hémorragie de l'intestin grêle caractéristiques de la forme systémique aiguë de l'AHD. L'immunohistochimie était positive pour OdAdV-1, confirmant le diagnostic. Le séquençage du génome entier du virus a été réalisé à des fins de comparaison phylogénétique. Il s'agit du premier cas signalé d'AHD chez un wapiti d'élevage au Canada et du premier cas signalé chez un wapiti en Alberta.Message clinique clé :La maladie hémorragique adénovirale (AHD) est une maladie émergente qui devrait être investiguée comme un diagnostic différentiel important lorsque les diagnosticiens et les vétérinaires rencontrent de jeunes cervidés trouvés morts avec un œdème pulmonaire ou une hémorragie et/ou une entéropathie hémorragique.(Traduit par Dr Serge Messier).

Characterization of neurotropic HPAI H5N1 viruses with novel genome constellations and mammalian adaptive mutations in free-living mesocarnivores in Canada.

The GsGd lineage (A/goose/Guangdong/1/1996) H5N1 virus was introduced to Canada in 2021/2022 through the Atlantic and East Asia-Australasia/Pacific flyways by migratory birds. This was followed by unprecedented outbreaks affecting domestic and wild birds, with spillover into other animals. Here, we report sporadic cases of H5N1 in 40 free-living mesocarnivore species such as red foxes, striped skunks, and mink in Canada. The clinical presentations of the disease in mesocarnivores were consistent with central nervous system infection. This was supported by the presence of microscopic lesions and the presence of abundant IAV antigen by immunohistochemistry. Some red foxes that survived clinical infection developed anti-H5N1 antibodies. Phylogenetically, the H5N1 viruses from the mesocarnivore species belonged to clade 2.3.4.4b and had four different genome constellation patterns. The first group of viruses had wholly Eurasian (EA) genome segments. The other three groups were reassortant viruses containing genome segments derived from both North American (NAm) and EA influenza A viruses. Almost 17 percent of the H5N1 viruses had mammalian adaptive mutations (E627 K, E627V and D701N) in the polymerase basic protein 2 (PB2) subunit of the RNA polymerase complex. Other mutations that may favour adaptation to mammalian hosts were also present in other internal gene segments. The detection of these critical mutations in a large number of mammals within short duration after virus introduction inevitably highlights the need for continually monitoring and assessing mammalian-origin H5N1 clade 2.3.4.4b viruses for adaptive mutations, which potentially can facilitate virus replication, horizontal transmission and posing pandemic risks for humans.

Divergent SARS-CoV-2 variant emerges in white-tailed deer with deer-to-human transmission.

Wildlife reservoirs of broad-host-range viruses have the potential to enable evolution of viral variants that can emerge to infect humans. In North America, there is phylogenomic evidence of continual transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from humans to white-tailed deer (Odocoileus virginianus) through unknown means, but no evidence of transmission from deer to humans. We carried out an observational surveillance study in Ontario, Canada during November and December 2021 (n = 300 deer) and identified a highly divergent lineage of SARS-CoV-2 in white-tailed deer (B.1.641). This lineage is one of the most divergent SARS-CoV-2 lineages identified so far, with 76 mutations (including 37 previously associated with non-human mammalian hosts). From a set of five complete and two partial deer-derived viral genomes we applied phylogenomic, recombination, selection and mutation spectrum analyses, which provided evidence for evolution and transmission in deer and a shared ancestry with mink-derived virus. Our analysis also revealed an epidemiologically linked human infection. Taken together, our findings provide evidence for sustained evolution of SARS-CoV-2 in white-tailed deer and of deer-to-human transmission.

Rapid and accurate SNP genotyping of clonal bacterial pathogens with BioHansel.

Hierarchical genotyping approaches can provide insights into the source, geography and temporal distribution of bacterial pathogens. Multiple hierarchical SNP genotyping schemes have previously been developed so that new isolates can rapidly be placed within pre-computed population structures, without the need to rebuild phylogenetic trees for the entire dataset. This classification approach has, however, seen limited uptake in routine public health settings due to analytical complexity and the lack of standardized tools that provide clear and easy ways to interpret results. The BioHansel tool was developed to provide an organism-agnostic tool for hierarchical SNP-based genotyping. The tool identifies split k-mers that distinguish predefined lineages in whole genome sequencing (WGS) data using SNP-based genotyping schemes. BioHansel uses the Aho-Corasick algorithm to type isolates from assembled genomes or raw read sequence data in a matter of seconds, with limited computational resources. This makes BioHansel ideal for use by public health agencies that rely on WGS methods for surveillance of bacterial pathogens. Genotyping results are evaluated using a quality assurance module which identifies problematic samples, such as low-quality or contaminated datasets. Using existing hierarchical SNP schemes for Mycobacterium tuberculosis and Salmonella Typhi, we compare the genotyping results obtained with the k-mer-based tools BioHansel and SKA, with those of the organism-specific tools TBProfiler and genotyphi, which use gold-standard reference-mapping approaches. We show that the genotyping results are fully concordant across these different methods, and that the k-mer-based tools are significantly faster. We also test the ability of the BioHansel quality assurance module to detect intra-lineage contamination and demonstrate that it is effective, even in populations with low genetic diversity. We demonstrate the scalability of the tool using a dataset of ~8100 S. Typhi public genomes and provide the aggregated results of geographical distributions as part of the tool's output. BioHansel is an open source Python 3 application available on PyPI and Conda repositories and as a Galaxy tool from the public Galaxy Toolshed. In a public health context, BioHansel enables rapid and high-resolution classification of bacterial pathogens with low genetic diversity.

Molecular Characterization of Southern African Territories 2 (SAT2) Serotype of Foot-and-Mouth Disease Virus from Nigeria in 2017 to 2018.

This report describes the nucleotide sequences of eight Southern African Territories 2 (SAT2) serotype foot-and-mouth disease virus strains from 2017 to 2018 outbreaks in cattle in Nigeria. These viruses belong to topotype VII of SAT2 and were closely related to previous isolates from Nigeria and other West African countries.

Discovery and comparative genomic analysis of elk circovirus (ElkCV), a novel circovirus species and the first reported from a cervid host.

The complete genome sequence of a novel circovirus (elk circovirus (ElkCV) Banff/2019) was determined via high throughput sequencing of liver tissue from a euthanized Rocky Mountain elk (Cervus canadensis nelsoni) from Alberta, Canada. The genome is circular and 1,787 nucleotides long, with two major ORFs encoding predicted proteins. Comparative genomic analysis to 4,164 publicly available complete and near complete circovirus genomes showed that ElkCV shares approximately 65% pairwise genome-wide nucleotide identity with the most closely related circovirus species, porcine circoviruses (PCV) 1 and 2 and bat-associated circovirus (BatACV) 11. ElkCV features a stem-loop within the origin of replication region characteristic of circoviruses. However, it differs from those found in PCV1, PCV2 and BatACV11 since it has a longer stem and contains hexamer repeats that overlap the stem in opposing orientations. Interestingly, stem-loop structures of similar length featuring repeats in a similar position and orientation are also seen in some avian circoviruses. Based on the demarcation threshold established by the International Committee on Taxonomy of Viruses (ICTV) for members of Circoviridae (80% pairwise genome-wide nucleotide identity), ElkCV represents a novel species and is the first complete circovirus genome reported from a cervid host.

Comprehensive assessment of the quality of Salmonella whole genome sequence data available in public sequence databases using the Salmonella in silico Typing Resource (SISTR).

Public health and food safety institutions around the world are adopting whole genome sequencing (WGS) to replace conventional methods for characterizing Salmonella for use in surveillance and outbreak response. Falling costs and increased throughput of WGS have resulted in an explosion of data, but questions remain as to the reliability and robustness of the data. Due to the critical importance of serovar information to public health, it is essential to have reliable serovar assignments available for all of the Salmonella records. The current study used a systematic assessment and curation of all Salmonella in the sequence read archive (SRA) to assess the state of the data and their utility. A total of 67 758 genomes were assembled de novo and quality-assessed for their assembly metrics as well as species and serovar assignments. A total of 42 400 genomes passed all of the quality criteria but 30.16 % of genomes were deposited without serotype information. These data were used to compare the concordance of reported and predicted serovars for two in silico prediction tools, multi-locus sequence typing (MLST) and the Salmonella in silico Typing Resource (SISTR), which produced predictions that were fully concordant with 87.51 and 91.91 % of the tested isolates, respectively. Concordance of in silico predictions increased when serovar variants were grouped together, 89.25 % for MLST and 94.98 % for SISTR. This study represents the first large-scale validation of serovar information in public genomes and provides a large validated set of genomes, which can be used to benchmark new bioinformatics tools.

A Genome-Wide Association Study to Identify Diagnostic Markers for Human Pathogenic Campylobacter jejuni Strains.

Campylobacter jejuni is a leading human enteric pathogen worldwide and despite an improved understanding of its biology, ecology, and epidemiology, limited tools exist for identifying strains that are likely to cause disease. In the current study, we used subtyping data in a database representing over 24,000 isolates collected through various surveillance projects in Canada to identify 166 representative genomes from prevalent C. jejuni subtypes for whole genome sequencing. The sequence data was used in a genome-wide association study (GWAS) aimed at identifying accessory gene markers associated with clinically related C. jejuni subtypes. Prospective markers (n = 28) were then validated against a large number (n = 3,902) of clinically associated and non-clinically associated genomes from a variety of sources. A total of 25 genes, including six sets of genetically linked genes, were identified as robust putative diagnostic markers for clinically related C. jejuni subtypes. Although some of the genes identified in this study have been previously shown to play a role in important processes such as iron acquisition and vitamin B5 biosynthesis, others have unknown function or are unique to the current study and warrant further investigation. As few as four of these markers could be used in combination to detect up to 90% of clinically associated isolates in the validation dataset, and such markers could form the basis for a screening assay to rapidly identify strains that pose an increased risk to public health. The results of the current study are consistent with the notion that specific groups of C. jejuni strains of interest are defined by the presence of specific accessory genes.

The Validation and Implications of Using Whole Genome Sequencing as a Replacement for Traditional Serotyping for a National Salmonella Reference Laboratory.

Salmonella serotyping remains the gold-standard tool for the classification of Salmonella isolates and forms the basis of Canada's national surveillance program for this priority foodborne pathogen. Public health officials have been increasingly looking toward whole genome sequencing (WGS) to provide a large set of data from which all the relevant information about an isolate can be mined. However, rigorous validation and careful consideration of potential implications in the replacement of traditional surveillance methodologies with WGS data analysis tools is needed. Two in silico tools for Salmonella serotyping have been developed, the Salmonella in silico Typing Resource (SISTR) and SeqSero, while seven gene MLST for serovar prediction can be adapted for in silico analysis. All three analysis methods were assessed and compared to traditional serotyping techniques using a set of 813 verified clinical and laboratory isolates, including 492 Canadian clinical isolates and 321 isolates of human and non-human sources. Successful results were obtained for 94.8, 88.2, and 88.3% of the isolates tested using SISTR, SeqSero, and MLST, respectively, indicating all would be suitable for maintaining historical records, surveillance systems, and communication structures currently in place and the choice of the platform used will ultimately depend on the users need. Results also pointed to the need to reframe serotyping in the genomic era as a test to understand the genes that are carried by an isolate, one which is not necessarily congruent with what is antigenically expressed. The adoption of WGS for serotyping will provide the simultaneous collection of information that can be used by multiple programs within the current surveillance paradigm; however, this does not negate the importance of the various programs or the role of serotyping going forward.

SuperPhy: predictive genomics for the bacterial pathogen Escherichia coli.

BACKGROUND: Predictive genomics is the translation of raw genome sequence data into a phenotypic assessment of the organism. For bacterial pathogens, these phenotypes can range from environmental survivability, to the severity of human disease. Significant progress has been made in the development of generic tools for genomic analyses that are broadly applicable to all microorganisms; however, a fundamental missing component is the ability to analyze genomic data in the context of organism-specific phenotypic knowledge, which has been accumulated from decades of research and can provide a meaningful interpretation of genome sequence data. RESULTS: In this study, we present SuperPhy, an online predictive genomics platform ( http://lfz.corefacility.ca/superphy/ ) for Escherichia coli. The platform integrates the analytical tools and genome sequence data for all publicly available E. coli genomes and facilitates the upload of new genome sequences from users under public or private settings. SuperPhy provides real-time analyses of thousands of genome sequences with results that are understandable and useful to a wide community, including those in the fields of clinical medicine, epidemiology, ecology, and evolution. SuperPhy includes identification of: 1) virulence and antimicrobial resistance determinants 2) statistical associations between genotypes, biomarkers, geospatial distribution, host, source, and phylogenetic clade; 3) the identification of biomarkers for groups of genomes on the based presence/absence of specific genomic regions and single-nucleotide polymorphisms and 4) in silico Shiga-toxin subtype. CONCLUSIONS: SuperPhy is a predictive genomics platform that attempts to provide an essential link between the vast amounts of genome information currently being generated and phenotypic knowledge in an organism-specific context.

Comparative Detection and Quantification of Arcobacter butzleri in Stools from Diarrheic and Nondiarrheic People in Southwestern Alberta, Canada.

Arcobacter butzleri has been linked to enteric disease in humans, but its pathogenicity and epidemiology remain poorly understood. The lack of suitable detection methods is a major limitation. Using comparative genome analysis, we developed PCR primers for direct detection and quantification ofA. butzleri DNA in microbiologically complex matrices. These primers, along with existing molecular and culture-based methods, were used to detectA. butzleri and enteric pathogens in stools of diarrheic and nondiarrheic people (n= 1,596) living in southwestern Alberta, Canada, from May to November 2008. In addition, quantitative PCR was used to compare A. butzleridensities in diarrheic and nondiarrheic stools.Arcobacter butzleriwas detected more often by PCR (59.6%) than by isolation methods (0.8%). Comparison by PCR-based detection found no difference in the prevalence ofA. butzleri between diarrheic (56.7%) and nondiarrheic (45.5%) individuals. Rates of detection in diarrheic stools peaked in June (71.1%) and October (68.7%), but there was no statistically significant correlation between the presence ofA. butzleri and patient age, sex, or place of habitation. Densities ofA. butzleriDNA in diarrheic stools (1.6 ± 0.59 log10 copies mg(-1)) were higher (P= 0.007) than in nondiarrheic stools (1.3 ± 0.63 log10copies mg(-1)). Of the 892 diarrheic samples that were positive for A. butzleri, 74.1% were not positive for other bacterial and/or viral pathogens. The current study supports previous work suggesting that A. butzleri pathogenicity is strain specific and/or dependent on other factors, such as the level of host resistance.

The Salmonella In Silico Typing Resource (SISTR): An Open Web-Accessible Tool for Rapidly Typing and Subtyping Draft Salmonella Genome Assemblies.

For nearly 100 years serotyping has been the gold standard for the identification of Salmonella serovars. Despite the increasing adoption of DNA-based subtyping approaches, serotype information remains a cornerstone in food safety and public health activities aimed at reducing the burden of salmonellosis. At the same time, recent advances in whole-genome sequencing (WGS) promise to revolutionize our ability to perform advanced pathogen characterization in support of improved source attribution and outbreak analysis. We present the Salmonella In Silico Typing Resource (SISTR), a bioinformatics platform for rapidly performing simultaneous in silico analyses for several leading subtyping methods on draft Salmonella genome assemblies. In addition to performing serovar prediction by genoserotyping, this resource integrates sequence-based typing analyses for: Multi-Locus Sequence Typing (MLST), ribosomal MLST (rMLST), and core genome MLST (cgMLST). We show how phylogenetic context from cgMLST analysis can supplement the genoserotyping analysis and increase the accuracy of in silico serovar prediction to over 94.6% on a dataset comprised of 4,188 finished genomes and WGS draft assemblies. In addition to allowing analysis of user-uploaded whole-genome assemblies, the SISTR platform incorporates a database comprising over 4,000 publicly available genomes, allowing users to place their isolates in a broader phylogenetic and epidemiological context. The resource incorporates several metadata driven visualizations to examine the phylogenetic, geospatial and temporal distribution of genome-sequenced isolates. As sequencing of Salmonella isolates at public health laboratories around the world becomes increasingly common, rapid in silico analysis of minimally processed draft genome assemblies provides a powerful approach for molecular epidemiology in support of public health investigations. Moreover, this type of integrated analysis using multiple sequence-based methods of sub-typing allows for continuity with historical serotyping data as we transition towards the increasing adoption of genomic analyses in epidemiology. The SISTR platform is freely available on the web at https://lfz.corefacility.ca/sistr-app/.

Development of a comparative genomic fingerprinting assay for rapid and high resolution genotyping of Arcobacter butzleri.

BACKGROUND: Molecular typing methods are critical for epidemiological investigations, facilitating disease outbreak detection and source identification. Study of the epidemiology of the emerging human pathogen Arcobacter butzleri is currently hampered by the lack of a subtyping method that is easily deployable in the context of routine epidemiological surveillance. In this study we describe a comparative genomic fingerprinting (CGF) method for high-resolution and high-throughput subtyping of A. butzleri. Comparative analysis of the genome sequences of eleven A. butzleri strains, including eight strains newly sequenced as part of this project, was employed to identify accessory genes suitable for generating unique genetic fingerprints for high-resolution subtyping based on gene presence or absence within a strain. RESULTS: A set of eighty-three accessory genes was used to examine the population structure of a dataset comprised of isolates from various sources, including human and non-human animals, sewage, and river water (n=156). A streamlined assay (CGF40) based on a subset of 40 genes was subsequently developed through marker optimization. High levels of profile diversity (121 distinct profiles) were observed among the 156 isolates in the dataset, and a high Simpson's Index of Diversity (ID) observed (ID > 0.969) indicate that the CGF40 assay possesses high discriminatory power. At the same time, our observation that 115 isolates in this dataset could be assigned to 29 clades with a profile similarity of 90% or greater indicates that the method can be used to identify clades comprised of genetically similar isolates. CONCLUSIONS: The CGF40 assay described herein combines high resolution and repeatability with high throughput for the rapid characterization of A. butzleri strains. This assay will facilitate the study of the population structure and epidemiology of A. butzleri.

Evaluation of MALDI-TOF mass spectroscopy methods for determination of Escherichia coli pathotypes.

It is rapidly becoming apparent that many E. coli pathotypes cause a considerable burden of human disease. Surveillance of these organisms is difficult because there are few or no simple, rapid methods for detecting and differentiating the different pathotypes. MALDI-TOF mass spectroscopy has recently been rapidly and enthusiastically adopted by many clinical laboratories as a diagnostic method because of its high throughput, relatively low cost, and adaptability to the laboratory workflow. To determine whether the method could be adapted for E. coli pathotype differentiation the Bruker Biotyper methodology and a second methodology adapted from the scientific literature were tested on isolates representing eight distinct pathotypes and two other groups of E. coli. A total of 136 isolates was used for this study. Results confirmed that the Bruker Biotyper methodology that included extraction of proteins from bacterial cells was capable of identifying E. coli isolates from all pathotypes to the species level and, furthermore, that the Bruker extraction and MALDI-TOF MS with the evaluation criteria developed in this work was effective for differentiating most pathotypes.

A framework for assessing the concordance of molecular typing methods and the true strain phylogeny of Campylobacter jejuni and C. coli using draft genome sequence data.

Tracking of sources of sporadic cases of campylobacteriosis remains challenging, as commonly used molecular typing methods have limited ability to unambiguously link genetically related strains. Genomics has become increasingly prominent in the public health response to enteric pathogens as methods enable characterization of pathogens at an unprecedented level of resolution. However, the cost of sequencing and expertise required for bioinformatic analyses remains prohibitive, and these comprehensive analyses are limited to a few priority strains. Although several molecular typing methods are currently widely used for epidemiological analysis of campylobacters, it is not clear how accurately these methods reflect true strain relationships. To address this, we have developed a framework and associated computational tools to rapidly analyze draft genome sequence data for the assessment of molecular typing methods against a "gold standard" based on the phylogenetic analysis of highly conserved core (HCC) genes with high sequence quality. We analyzed 104 publicly available whole genome sequences (WGS) of C. jejuni and C. coli. In addition to in silico determination of multi-locus sequence typing (MLST), flaA, and porA type, as well as comparative genomic fingerprinting (CGF) type, we inferred a "reference" phylogeny based on 389 HCC genes. Molecular typing data were compared to the reference phylogeny for concordance using the adjusted Wallace coefficient (AWC) with confidence intervals. Although MLST targets the sequence variability in core genes and CGF targets insertions/deletions of accessory genes, both methods are based on multi-locus analysis and provided better estimates of true phylogeny than methods based on single loci (porA, flaA). A more comprehensive WGS dataset including additional genetically related strains, both epidemiologically linked and unlinked, will be necessary to more comprehensively assess the performance of subtyping methods for outbreak investigations and surveillance activities. Analyses of the strengths and weaknesses of widely used typing methodologies in inferring true strain relationships will provide guidance in the interpretation of this data for epidemiological purposes.

Development and validation of a comparative genomic fingerprinting method for high-resolution genotyping of Campylobacter jejuni.

Campylobacter spp. are a leading cause of bacterial gastroenteritis worldwide. The need for molecular subtyping methods with enhanced discrimination in the context of surveillance- and outbreak-based epidemiologic investigations of Campylobacter spp. is critical to our understanding of sources and routes of transmission and the development of mitigation strategies to reduce the incidence of campylobacteriosis. We describe the development and validation of a rapid and high-resolution comparative genomic fingerprinting (CGF) method for C. jejuni. A total of 412 isolates from agricultural, environmental, retail, and human clinical sources obtained from the Canadian national integrated enteric pathogen surveillance program (C-EnterNet) were analyzed using a 40-gene assay (CGF40) and multilocus sequence typing (MLST). The significantly higher Simpson's index of diversity (ID) obtained with CGF40 (ID = 0.994) suggests that it has a higher discriminatory power than MLST at both the level of clonal complex (ID = 0.873) and sequence type (ID = 0.935). High Wallace coefficients obtained when CGF40 was used as the primary typing method suggest that CGF and MLST are highly concordant, and we show that isolates with identical MLST profiles are comprised of isolates with distinct but highly similar CGF profiles. The high concordance with MLST coupled with the ability to discriminate between closely related isolates suggests that CFG40 is useful in differentiating highly prevalent sequence types, such as ST21 and ST45. CGF40 is a high-resolution comparative genomics-based method for C. jejuni subtyping with high discriminatory power that is also rapid, low cost, and easily deployable for routine epidemiologic surveillance and outbreak investigations.